Topics of interest of the CCBD2016 conference include, but are not limited to:

Architecture & Foundation of Cloud Computing and Big Data

• Infrastructure as a Service, Green Cloud Computing, Monitoring, Management and Maintenance of Cloud Platform

• Service-Oriented Architectures in cloud computing

• Software Defined Storage, Software Defined Network, and Software Defined Data Center

• Performance Improvement and Hardware Optimizations for Cloud Computing and Big Data

• Integrated Platform for Cloud Computing, Big Data, IoT and Social Networks

• Sensors, Devices and Embedded Systems Design in Cloud Computing

• Energy-efficient Cloud Computing for Big Data

• Open Platforms and System Architectures to Support Big Data

• Novel Theoretical and Computational Models for Big Data

• Best Practices for Migration to Cloud

Software Engineering, Tools & Services for Cloud Computing and Big Data

• Platform as a Service, DevOps, and API Management

• Software Engineering in Cloud Computing

• Job Scheduling, Load Balancing, Performance Evaluation & Improvement in Cloud Computing

• Novel Data Model and Databases for Emerging Hardware to Support Big Data

• Information Integration and Heterogeneous and Multi-structured Data Integration

• Novel Programming Model, Quality Measurement, Evaluation and Management

• Information lifecycle management for Cloud Computing and Big Data

• Business Process and Workflow Management in Cloud Services

• Innovative Cloud Applications, Novel Theoretical and Computational Models for Big Data

Knowledge Discovery & Data Engineering in Cloud Computing and Big Data

• Big Data Information Life Cycle Management

• Social Web Search and Mining

• Algorithms for Big Data Search

• Big Data Search Architectures, Scalability and Efficiency

• Big Data Analytic Algorithms, Knowledge Discovery & Data Engineering

• Visualization Analytics for Big Data

• Computational Modeling and Data Integration

• Large Scale Distributed, Knowledge Management

• Large-scale Recommendation Systems and Social Media Systems

• Cloud/Grid/Stream Data Mining - Big Velocity Data

• Multimedia and Multi-Structured Data - Big Variety Data

• Internet-Based Knowledge Engineering in Cloud Computing

Security, Privacy, Trust & Quality of Cloud Computing and Big Data

• Hardware/Software Reliability, Verification and Testing in Cloud Computing and Big Data

• Trusted Computing & Autonomic Computing in Cloud Computing and Big Data

• Fault Tolerance in Cloud Computing and Big Data

• Security and Privacy in Cloud Computing and Big Data

• Threat Detection using Big Data Analytics

• Privacy Preserving Big Data Collection/Analytics

• HCI Challenges for Big Data Security & Privacy

• Protection, Integrity and Privacy Standards and Policies for Big data

Business Models and Applications for Cloud Computing and Big Data

• Innovative Business Models and Applications of Cloud Computing and Big Data in Different Domains

• API Management, API Ecosystem, and API Economy

• Industrial IoT and Analytics